How do I install Ppl?

Ppl is a remote plugin. You do not need to install anything locally. Add the server URL to your AI app's MCP configuration and you are ready to go.

Yes. Ppl passed MCP Marketplace's automated security scan with a score of 10/10 (low risk). Every server on MCP Marketplace is security-scanned before it's listed; see the full security report on this page for the findings and permissions.

What AI apps work with Ppl?

Ppl uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Ppl MCP Server

by Ppl Crm

Developer ToolsLow Risk10.0MCP RegistryRemote

Free

Server data from the Official MCP Registry

ppl: the personal CRM for AI agents. Structured relationship memory over hosted MCP.

About

ppl: the personal CRM for AI agents. Structured relationship memory over hosted MCP.

Remote endpoints: streamable-http: https://withppl.com/mcp

Security Report

10.0

Low Risk10.0Low Risk

Valid MCP server (2 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

Endpoint verified · Requires authentication · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Found in Source Code

Found by scanning the linked source code. This listing connects to a hosted endpoint, so none of this runs on your machine: it describes what the server software does where it is hosted.

env_vars

Applies to the server that hosts this plugin, not to your machine.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "io-github-ppl-crm-ppl": {
      "url": "https://withppl.com/mcp"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

ppl

Relational memory for you and your AI.

ppl is the personal CRM for humans with AI agents. Your relationships, notes, journal, tasks, and reminders live here. Your AI reads from it before acting, and writes to it after acting.

Connect your AI

Hosted MCP server: https://withppl.com/mcp

ppl is hosted-only. There is no downloadable server. Your agent connects over Streamable HTTP with a Bearer token.

One-click setup

Send your human to withppl.com/agents. If they use Cursor and are logged in, it's one click. New users get an account created inline, no signup form first.

Agent connection flow

POST https://withppl.com/api/agent/connect/request with {"client_name": "Your agent"}
Show the human the approve_url. They approve once (creating an account inline if needed).
Poll the poll_url until approved and save the api_token.
Use the token with the MCP server or REST API.

Full machine-readable spec: withppl.com/.well-known/ppl.json

MCP registry

Registered as io.github.ppl-crm/ppl in the official MCP registry. See server.json.

Examples

Python MCP client - connect with the MCP Python SDK
Node MCP client - connect with the MCP TypeScript SDK
ppl-memory PyPI package - LangGraph, CrewAI, and AutoGen adapters

Docs

Agent integration guide - session prescription, tools, and patterns
OAuth for MCP clients - Dynamic Client Registration flow

License

MIT. See LICENSE.

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